Performance analysis of a novel heavy oil recovery process using in-situ steam generated by thermochemicals

Heavy oil has attracted global attention due to its huge volume of original oil in place. However, there are numerous operation and economic challenges during the recovery of heavy oil due to its high-viscosity and high-density. Thermal recovery methods such as steam injection is viable and commonly used to recover heavy oil and bitumen primarily by thermally altering oil viscosity and improving the displacement of heavy oil. However, there are significant heat losses before the steam reaches the heavy oil, in addition to the concerns of high cost and emission of greenhouse gases. One of the promising new heavy oil recovery approaches is generating steam, in-situ, using chemical reaction to reduce the oil viscosity, improve the mobility ratio, and enhance the heavy oil displacement. The objective of this work is to introduce a novel heavy oil recovery process using in-situ steam generated by thermal and chemical reaction and analyze its recovery performance compared with conventional steam injection method from the economic point of view, as well as based on the achieved net present value (NPV) of each technique. Sensitivity analysis of the proposed recovery processes to different operational parameters is introduced. The CMG STARS™ Simulator is used in this work to simulate reservoir models with different operational parameters. The recovery performance of the proposed technique outperformed the conventional steam flooding method and achieved higher NPV after ten years of production. This is the first time to use NPV and consider all economic parameters to analyze the performance of the developed recovery process of in-situ steam generation by chemical reaction. This research shows that the recovery of the proposed method is economic, and applicable to the reservoirs which are not viable for conventional steam flooding methods and it is a step forward to eliminate CO₂ emissions associated with thermal recovery processes.